The Depressed Decision Maker: The Application of Decision Science to Psychopathology

Is decision making impaired in mental illness populations? Can behavioral economics provide insight into clinical psychology? The present project addresses these broad questions through three studies. In the first study, two meta-analyses were conducted of experiments that used the Iowa Gambling Task (IGT) to assess value based decision making in populations with mental illness. In the first meta-analysis (63 studies, combined N = 4,978), we compared IGT performance in healthy populations and populations with mental illness. In the second meta-analysis (40 studies, combined N = 1,813), we examined raw IGT performance scores as a function of type of mental illness. The first meta-analysis demonstrated that individuals with mental illness performed significantly worse than did healthy control individuals. The second meta-analysis demonstrated no performance differences based on type of mental illness. Impairment on the IGT, however, could indicate effects from several different decision processes. Accordingly, in the second study, using multiple decision tasks we explored different aspects of decision making in a single group that exhibited reliable effects in the meta-analysis, major depressive disorder. The second study answers three questions. First, how does decision making differ in clinically depressed individuals across a range of decision tasks? Second, where are the largest differences between clinically depressed and non-depressed individuals? And finally, how well can decision task performance discriminate depressed individuals from healthy controls? Depressed individuals\u27 decision-making was significantly different across a range of decision tasks, but impaired learning and pessimism bias showed the strongest behavioral signature of depression. Decision tasks significantly predict depression, but are far outperformed by self-report measures as diagnostic tools. Overall, results suggest decision tasks are better suited to identify specific impaired processes rather than for diagnostic prediction. This study suggested depression is associated with impaired reward and punishment processing, but what are the underlying causes behind these deficits? In the third study, we performed a detailed analysis of reward and punishment learning in clinically depressed individuals, quantifying choice behavior by fitting reinforcement learning models. The results suggest that depression is characterized by hyposensitivity to reward. The reinforcement learning models show that depressed individuals engage habit-oriented model-free learning strategies in contrast to the goal-oriented model-based strategies engaged by healthy controls. Overall the three studies demonstrate how interdisciplinary research combining decision science and clinical psychology can help to better understand mental illness

Nonhuman gamblers: lessons from rodents, primates, and robots

The search for neuronal and psychological underpinnings of pathological gambling in humans would benefit from investigating related phenomena also outside of our species. In this paper, we present a survey of studies in three widely different populations of agents, namely rodents, non-human primates, and robots. Each of these populations offers valuable and complementary insights on the topic, as the literature demonstrates. In addition, we highlight the deep and complex connections between relevant results across these different areas of research (i.e., cognitive and computational neuroscience, neuroethology, cognitive primatology, neuropsychiatry, evolutionary robotics), to make the case for a greater degree of methodological integration in future studies on pathological gambling

Dissociation of Response and Feedback Negativity in Schizophrenia: Electrophysiological and Computational Evidence for a Deficit in the Representation of Value

Contrasting theories of schizophrenia propose that the disorder is characterized by a deficit in phasic changes in dopamine activity in response to ongoing events or, alternatively, by a weakness in the representation of the value of responses. Schizophrenia patients have reliably reduced brain activity following incorrect responses but other research suggests that they may have intact feedback-related potentials, indicating that the impairment may be specifically response-related. We used event-related brain potentials and computational modeling to examine this issue by comparing the neural response to outcomes with the neural response to behaviors that predict outcomes in patients with schizophrenia and psychiatrically healthy comparison subjects. We recorded feedback-related activity in a passive gambling task and a time estimation task and error-related activity in a flanker task. Patients’ brain activity following an erroneous response was reduced compared to comparison subjects but feedback-related activity did not differ between groups. To test hypotheses about the possible causes of this pattern of results, we used computational modeling of the electrophysiological data to simulate the effects of an overall reduction in patients’ sensitivity to feedback, selective insensitivity to positive or negative feedback, reduced learning rate, and a decreased representation of the value of the response given the stimulus on each trial. The results of the computational modeling suggest that schizophrenia patients exhibit weakened representation of response values, possibly due to failure of the basal ganglia to strongly associate stimuli with appropriate response alternatives

Loss of control over eating : A systematic review of task based research into impulsive and compulsive processes in binge eating

Recurring episodes of excessive food intake in binge eating disorder can be understood through the lens of behavioral control systems: patients repeat maladaptive behaviors against their explicit intent. Self-report measures show enhanced impulsivity and compulsivity in binge eating (BE) but are agnostic as to the processes that might lead to impulsive and compulsive behavior in the moment. Task-based neurocognitive investigations can tap into those processes. In this systematic review, we synthesize neurocognitive research on behavioral impulsivity and compulsivity in BE in humans and animals, published between 2010-2020. Findings on impulsivity are heterogeneous. Findings on compulsivity are sparse but comparatively consistent, indicating an imbalance of goal-directed and habitual control as well as deficits in reversal learning. We urge researchers to address heterogeneity related to mood states and the temporal dynamics of symptoms, to systematically differentiate contributions of body weight and BE, and to ascertain the validity and reliability of tasks. Moreover, we propose to further scrutinize the compulsivity findings to unravel the computational mechanisms of a potential reinforcement learning deficit.Peer reviewe

Slot Machine Use As A Measure Of Decision-Making In Substance Use Disorders

Many of the decision-making tasks involve gambling and gambling paradigms and therefore it is important to understand how gambling relates to decision-making, especially in individuals who use substances. The goal of this study was to investigate how individuals with SUD will perform on a slot machine and relate the slot-machine performance to current lab measures of decision-making. Individuals with and without substance use disorders gambled on a slot machine and completed other decision-making tasks (e.g., IGT, BART, delay discounting). Rewards were manipulated in terms of magnitude (real monetary payout verses no payout) for two reasons. Gambling performance was compared to three common lab measures of decision-making (i.e., IGT, BART, & delay discounting). In addition, measures of substance use and gambling motivation were obtained to relate the slot-machine paradigm to meaningful reasons for engaging in addictive behaviors. There were four main findings in this study. First, all participants tended to bet more tokens per trial on the slot machine when there was no monetary compensation compared to if there was. Second, no group or magnitude differences were found on any of the decision-making tasks (i.e., IGT, BART, and delay discounting). Third, the slot machine and all the decision-making task seems to be relatively independent from each other. Fourth, performance on the slot machine and the decision-making tasks was able to predict using alcohol for positive reinforcement, in particular, for social situations and enhancing positive feelings and experiences. It is important that future research investigates decision making 1) uses multiple measures of decision making to access potentially different aspect of decision-making and 2) flesh out the differences between these tasks and find out what these tasks are able to detect

Enhanced Risk Aversion, But Not Loss Aversion, in Unmedicated Pathological Anxiety.

BACKGROUND: Anxiety disorders are associated with disruptions in both emotional processing and decision making. As a result, anxious individuals often make decisions that favor harm avoidance. However, this bias could be driven by enhanced aversion to uncertainty about the decision outcome (e.g., risk) or aversion to negative outcomes (e.g., loss). Distinguishing between these possibilities may provide a better cognitive understanding of anxiety disorders and hence inform treatment strategies. METHODS: To address this question, unmedicated individuals with pathological anxiety (n = 25) and matched healthy control subjects (n = 23) completed a gambling task featuring a decision between a gamble and a safe (certain) option on every trial. Choices on one type of gamble-involving weighing a potential win against a potential loss (mixed)-could be driven by both loss and risk aversion, whereas choices on the other type-featuring only wins (gain only)-were exclusively driven by risk aversion. By fitting a computational prospect theory model to participants' choices, we were able to reliably estimate risk and loss aversion and their respective contribution to gambling decisions. RESULTS: Relative to healthy control subjects, pathologically anxious participants exhibited enhanced risk aversion but equivalent levels of loss aversion. CONCLUSIONS: Individuals with pathological anxiety demonstrate clear avoidance biases in their decision making. These findings suggest that this may be driven by a reduced propensity to take risks rather than a stronger aversion to losses. This important clarification suggests that psychological interventions for anxiety should focus on reducing risk sensitivity rather than reducing sensitivity to negative outcomes per se

The motivation and pleasure dimension of negative symptoms: neural substrates and behavioral outputs.

A range of emotional and motivation impairments have long been clinically documented in people with schizophrenia, and there has been a resurgence of interest in understanding the psychological and neural mechanisms of the so-called "negative symptoms" in schizophrenia, given their lack of treatment responsiveness and their role in constraining function and life satisfaction in this illness. Negative symptoms comprise two domains, with the first covering diminished motivation and pleasure across a range of life domains and the second covering diminished verbal and non-verbal expression and communicative output. In this review, we focus on four aspects of the motivation/pleasure domain, providing a brief review of the behavioral and neural underpinnings of this domain. First, we cover liking or in-the-moment pleasure: immediate responses to pleasurable stimuli. Second, we cover anticipatory pleasure or wanting, which involves prediction of a forthcoming enjoyable outcome (reward) and feeling pleasure in anticipation of that outcome. Third, we address motivation, which comprises effort computation, which involves figuring out how much effort is needed to achieve a desired outcome, planning, and behavioral response. Finally, we cover the maintenance emotional states and behavioral responses. Throughout, we consider the behavioral manifestations and brain representations of these four aspects of motivation/pleasure deficits in schizophrenia. We conclude with directions for future research as well as implications for treatment

Family History of Substance Use Disorders: Significance for Mental Health in Young Adults who Gamble?

Background: Although family history of psychiatric disorders has often been considered potentially useful in understanding clinical presentations in patients, it is less clear what a positive family history means for people who gamble in the general community. We sought to understand the clinical and cognitive impact of having a first-degree relative with a substance use disorder (SUD) in a sample of non-treatment seeking young adults. Methods: 576 participants (aged 18-29 years) who gambled at least 5 times in the preceding year undertook clinical and neurocognitive evaluations. Those with a first-degree relative with a SUD were compared to those without on a number of demographic, clinical and cognitive measures. We used Partial Least Squares regression (PLS) to identify which variables (if any) were significantly associated with family history of SUDs, controlling for the influence of other variables on each other. Results: 180 (31.3%) participants had a first-degree family member with a SUD. In terms of clinical variables, family history of SUD was significantly associated with higher rates of substance use (alcohol, nicotine), higher rates of problem gambling, and higher occurrence of mental health disorders. Family history of SUD was also associated with more set-shifting problems (plus higher rates of obsessive-compulsive tendencies), lower quality of decision-making, and more spatial working memory errors. Conclusions: These results indicate that gamblers with a first-degree family member with a SUD may have a unique clinical and cognition presentation. Understanding these differences may be relevant to developing more individualized treatment approaches for disordered gambling. Compulsivity may be important as a proxy of vulnerability towards addiction

Computational Models Describe Individual Differences in Cognitive Function and Their Relationships to Mental Health Symptoms

Cognitive alterations have long been reported in patients with mental health disorders, though with inconsistent results. These inconsistencies are likely due to highly heterogeneous diagnostic categories used for recruitment, and imprecise cognitive task measures. This thesis addresses the former by measuring symptoms with continuous questionnaire scales, and the latter by using theory- driven computational models that summarise participant behaviour using a small number of mechanistic parameters. This methodology is applied within the realm of attention set shifting and risky decision making to improve understanding of cognition in mental health, using large samples collected online. Following a general introduction (Chapter 1), Chapter 2 describes the computational approach employed in subsequent experimental chapters. In Chapter 3, we develop models of CANTAB IED (Intra-Extra Dimensional Set Shifting Task) to explore how learning and attention processes lead to differences in attention set shifting ability, and to investigate their relationship with symptoms of compulsivity. The second study (Chapter 4) applies the computational approach to risky decisions with CANTAB CGT (Cambridge Gamble Task) and explores the relationship between model parameters and symptoms of depression and anxiety. The final experimental chapter (Chapter 5) examines whether specific symptoms of anxiety are related to changes in risky decision making, focusing on the relationship between catastrophising and probability weighting. Overall, the computational approach offers increased precision when examining behavioural data. In several chapters we identify moderate relationships between model parameters and demographic variables such as age, gender, and level of education, which often exceed associations with traditional model- agnostic measures. However, relationships with mental health symptoms are minimal in the general population datasets tested here. The general discussion (Chapter 6) considers these findings in relation to the wider field of computational psychiatry, discussing both the limitations of the work presented and possible future directions

Decision-making (in)flexibility in gambling disorder

Background: Behavioral flexibility –the ability to dynamically readjust our behavior in response to reward contingency changes– is often investigated using probabilistic reversal learning tasks (PRLT). Poor PRLT performance has been proposed as a proxy for compulsivity, and theorized to be related to perseverative gambling. Previous attempts to measure inflexibility with the PRLT in patients with gambling disorder have, however, used a variety of indices that may conflate inflexibility with more general aspects of performance in the task. Methods: Trial-by-trial PRLT acquisition and reacquisition curves in 84 treatment-seeking patients with gambling disorder and 64 controls (non-gamblers and non-problem recreational gamblers) were analyzed to distinguish between (a) variability in acquisition learning, and (b) reacquisition learning in reversed contingency phases. Complementarily, stay/switch responses throughout the task were analyzed to identify (c) premature switching, and (d) sensitivity to accumulated negative feedback. Results and interpretation: Even after controlling for differences in acquisition learning, patients were slower to readjust their behavior in reversed contingency phases, and were more prone to maintain their decisions despite accumulated negative feedback. Inflexibility in patients with gambling disorder is thus a robust phenomenon that could predate gambling escalation, or result from massive exposure to gambling activities.This work was supported by grants from the Spanish Government (PSI2017-85488-P: Ministerio de Economía y Competitividad, Secretaría de Estado de Investigación, Desarrollo e Innovación, Convocatoria 2017 de Proyectos I+ D de Excelencia, Spain, co-funded by the Fondo Europeo de Desarrollo Regional, FEDER, European Commission; and PSI2013-45055: Ministerio de Economía y Competitividad, Secretaría de Estado de Invetigación, Desarrollo e Innovación, Convocatoria 2013 de Proyectos I+ D de Excelencia). Additionally, JFN was supported by a grant from the Spanish Government (PSI2017-85159-P. Ministerio de Ciencia, Innovación y Universidades). Funding agencies had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication